Slides – http://bit.ly/IQT16

This work is released under Creative Commons

  • About me
    • I solely maintain and develop plotly's R package (part time).
    • PhD in statistics from Iowa State University (ABD).
    • Expert in the intersection of R, web technologies, and data visualization.
    • Novice disease outbreak analyst.
  • Why R?
    • R is a free and open-source statistical programming language.
    • A huge community:
      • Over 9000 user contributed packages currently on CRAN (best source for latest statistical methodology)
      • The package surveillance implements outbreak detection methods from 13 different publications!
      • Numerous organization support R development (R Consortium, RStudio, rOpenSci, etc)

About plotly

  • R package builds upon plotly.js (open-source JavaScript graphing library)
  • Plotly has other interfaces to plotly.js (Python, Julia, MATLAB, Ruby).
  • Share, collaborate, & modify via web platform (public: free, private: costs)

An example

library(plotly)
plot_ly(measles, x = ~date, y = ~count, color = ~district, mode = "lines")

What if there are many areas of interest?

Visualization mantras

Statistical graphics perspective:

Visualizations can surprise you, but don't scale well. Modeling scales well, but can't surprise you.

— Hadley Wickham

Information visualization perspective:

Overview first, then zoom and filter, then details on demand.

— Ben Shneiderman

Zika Exploration App

Thank you!